Ultra-precision cutting surface geometrical morphology and machining precision prediction method

Abstract

The invention belongs to the technical field of ultra-precision machining, and discloses an ultra-precision cutting surface geometrical morphology and machining precision prediction method which comprises the steps that machining parameters, cutter parameters and material parameters are obtained; a cutting edge contour of the tool is established according to the tool parameters, contour deformation caused by material elastic recovery is calculated according to the machining parameters and the material parameters, and contour deformation caused by plastic lateral flow is calculated according to the machining parameters, the tool parameters and the material parameters; on the basis of the cutting edge contour of the tool, the deformation caused by material elastic recovery and the deformation caused by plastic lateral flow, the correction coefficient of the shape prediction model under different machining parameters is calculated, and a cutting surface geometric shape prediction model is obtained; and the machining parameters are optimized and corrected, the elasticoplastic deformation is pre-compensated, and the final cutting surface is obtained. According to the method, the contour of the cutting edge of the cutter, the elastic recovery and the plastic lateral flow are comprehensively considered into the surface topography model, so that the prediction precision of the microstructure surface topography model is effectively improved.

Description

Technical Field

[0001] The invention relates to the technical field of ultra-precision machining, and in particular to a method for predicting the geometrical morphology and machining accuracy of an ultra-precision cutting surface. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Single-point diamond turning is a cutting technology used to process high-precision surfaces, which can directly obtain sub-micron-level surface topography. Since its cutting depth is several microns, the influence of microscopic factors such as edge bluntness, material elastic recovery and plastic side flow on the processing accuracy must be considered.

[0004] Tool profile replication is an important method for diamond turning microstructures. For the predictive modeling of the surface morphology of ultra-precision turning microstructures, only the tool profile and cutting trajectory are usually considered. However, due to the influence of material elastic recovery and plastic flow, there is a geometric deviation between the actual surface morphology of the workpiece and the tool cutting edge profile. Figure 2 Schematic diagram of the effect of material elastic-plastic deformation on the cross-sectional profile of diamond microgrooves. At present, there is no definite elastic-plastic deformation model for diamond cutting microstructures, and it is impossible to accurately predict the deformation law of the workpiece material affected by the cutting force, tool geometry parameters and material flow characteristics, resulting in a significant deviation between the actual machined surface morphology and the design target. In the theoretical model of the surface morphology of ultra-precision cutting planes, elastic recovery is usually attributed to the minimum cutting thickness corresponding to the blunt edge, but this theory is not applicable to microstructure processing. At the same time, the theoretical model of plastic lateral flow in the cutting plane is not applicable to microstructure processing.

[0005] Due to the existence of the above problems, a modeling method that can accurately predict the contour error caused by elastic-plastic deformation is needed to guide the optimization of diamond turning processing parameters and improve its processing accuracy. Summary of the invention

[0006] In order to solve the above problems, the present invention proposes a method for predicting the geometric morphology and machining accuracy of ultra-precision cutting surfaces, which comprehensively considers the tool cutting edge profile, elastic recovery and plastic lateral flow into the surface morphology model, effectively improving the prediction accuracy of the microstructure surface morphology model.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface, comprising the following steps:

[0009] Obtaining machining parameters, tool geometry parameters and characteristic parameters of the workpiece material to be cut;

[0010] The cutting edge profile of the tool is established according to the tool geometric parameters, the profile deformation caused by the elastic recovery of the material is calculated according to the processing parameters and the characteristic parameters of the workpiece material to be cut, and the profile deformation caused by the plastic lateral flow is calculated according to the processing parameters, the tool geometric parameters and the characteristic parameters of the workpiece material to be cut;

[0011] Based on the cutting edge profile of the tool, the deformation caused by the elastic recovery of the material, and the deformation caused by the plastic lateral flow, the correction coefficient of the morphology prediction model under different processing parameters is calculated to obtain the cutting surface geometric morphology prediction model;

[0012] The machining parameters are optimized and modified, and the elastic-plastic deformation is pre-compensated to obtain the final cutting surface.

[0013] As an optional implementation, the cutting edge profile of the tool is established according to the tool geometric parameters, specifically:

[0014] R t =R ideal +ΔR wave =R ideal +Δwsin(ωθ)

[0015] Among them, R ideal is the ideal cutting edge profile of the tool, and Δw is the cutting edge waviness amplitude.

[0016] As an alternative embodiment, the ideal cutting edge profile of a circular arc tool with a radius r can be calculated by the following formula:

[0017]

[0018] The blade tip angle is The ideal cutting edge profile of a V-tip knife can be calculated by the following formula:

[0019]

[0020] Where h is the cutting depth.

[0021] As an optional embodiment, the contour deformation caused by the elastic recovery of the material includes the elastic recovery caused by the cutting force and the elastic recovery caused by the blunting of the cutting edge.

[0022] As an optional embodiment, the contour deformation amount caused by the plastic lateral flow includes the reduction amount of the micro-groove width caused by the plastic lateral flow and the material accumulation at the micro-groove boundary caused by the plastic lateral flow.

[0023] As an optional implementation, the final cutting surface geometry prediction model is:

[0024] R model =R t +f d f s f m (e+s+Δh a )

[0025] Among them, f d is the correction factor of the prediction model regarding cutting depth, f s is the correction factor of the prediction model for cutting speed, f m is the correction factor of the prediction model regarding the workpiece material.

[0026] As an optional embodiment, the tool geometric parameters include the arc radius of the arc-shaped tool, the angle of the V-shaped tip, the front angle and the back angle of the tool, and the waviness of the cutting edge profile.

[0027] As an optional implementation, the characteristic parameters of the workpiece material to be cut include elastic modulus, Poisson's ratio, hardness and yield strength.

[0028] As an optional embodiment, the calculation formula for the material accumulation height at the microgroove boundary caused by plastic lateral flow is:

[0029]

[0030] in, Represents the equivalent half apex angle of the diamond tool.

[0031] As an optional embodiment, the calculation formula for the reduction in microgroove width caused by plastic lateral flow is:

[0032] s=k c k m k t h min L t

[0033] Among them, k c is the correction factor, k m is a coefficient determined by material properties, k t is a coefficient determined by the tool size, L t is the cutting width of the tool.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention discloses a method for predicting the geometric morphology and machining accuracy of ultra-precision cutting surfaces, studies the influence of material elastic-plastic deformation on the micro-groove cross-sectional profile, and effectively improves the prediction accuracy of the microstructure surface morphology model by comprehensively considering the tool cutting edge profile, elastic recovery and plastic lateral flow into the surface morphology prediction model. For metal materials, the average error of the micro-groove cross-sectional profile prediction is controlled within 0.08μm, and the maximum error does not exceed 0.30μm. Accurately predict the morphology error before machining, pre-compensate the machining error by optimizing the machining parameters, and further improve the machining accuracy of ultra-precision cutting.

[0036] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0038] Figure 1 A flow chart of the method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface provided in Example 1 of the present invention;

[0039] Figure 2 Schematic diagram of the effect of elastic-plastic deformation of materials on the cross-sectional profile of diamond microgrooves;

[0040] Figure 3 The tool cutting edge profile measurement results obtained using an optical microscope, where (a) is the measurement result of an arc-shaped tool with a nominal radius of 100 μm, (b) is the measurement result of an arc-shaped tool with a nominal radius of 50 μm, and (c) is the measurement result of a V-shaped sharp tool with a nominal angle of 140°;

[0041] Figure 4 Schematic diagram of the influence of the elastic recovery component on the cross-sectional profile in the model of the present invention, wherein (a) is the elastic recovery corresponding to the contact pressure of the arc-shaped tool on the workpiece, (b) is the elastic recovery corresponding to the contact pressure of the V-shaped tool on the workpiece, (c) is the elastic recovery corresponding to the bluntness of the arc-shaped tool edge, and (d) is the elastic recovery corresponding to the bluntness of the V-shaped tool edge;

[0042] Figure 5 Schematic diagram of the influence of the plastic lateral flow component on the cross-sectional profile in the model of the present invention, wherein (a) is the plastic lateral flow generated by using a circular arc-shaped tool, and (b) is the plastic lateral flow generated by using a V-shaped sharp tool;

[0043] Figure 6 A schematic diagram of selecting a correction coefficient according to different processing parameters in the present invention;

[0044] Figure 7 A comparison diagram of the prediction results and the experimental results of the first embodiment of the ultra-precision turning microstructure surface morphology modeling method of the present invention;

[0045] Figure 8 A comparison diagram of the prediction results and experimental results of the second embodiment of the ultra-precision turning microstructure surface morphology modeling method of the present invention;

[0046] Fig. 9 This is a comparison chart between the prediction results and the experimental results of Example 3 of the ultra-precision turning microstructure surface morphology modeling method of the present invention. DETAILED DESCRIPTION

[0047] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0048] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0049] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "include" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0050] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0051] Example 1

[0052] like Figure 1 As shown, this embodiment provides a method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface, comprising the following steps:

[0053] S1, obtaining machining parameters, tool geometry parameters and characteristic parameters of the workpiece material to be cut;

[0054] S2. Establishing a cutting edge profile of the tool according to the tool geometry parameters, calculating the profile deformation caused by the elastic recovery of the material according to the machining parameters and the characteristic parameters of the workpiece material to be cut, and calculating the profile deformation caused by the plastic lateral flow according to the machining parameters, the tool geometry parameters and the characteristic parameters of the workpiece material to be cut;

[0055] S3, based on the cutting edge profile of the tool, the deformation caused by the elastic recovery of the material and the deformation caused by the plastic lateral flow, the correction coefficient of the morphology prediction model under different processing parameters is calculated to obtain the cutting surface geometric morphology prediction model;

[0056] S4. Optimize and modify the processing parameters, pre-compensate the elastic-plastic deformation, and obtain the final cutting surface.

[0057] Before obtaining the tool geometry parameters, you first need to clean the tip of the diamond tool. Use a dust-free clean cotton swab dipped in acetone or ethanol to wipe the front and back surfaces until no stains or dust can be seen at a total magnification of 500 times. Use an optical microscope or a scanning electron microscope to obtain a top view of the front surface at the tool tip. Use a digital image processing algorithm to calculate the tool geometry parameters and obtain the arc radius r of the arc tool and the angle of the V-shaped tip. Determine the rake angle and relief angle, use atomic force microscopy to obtain the waviness of the cutting edge profile, and use optical microscopy to obtain the tool cutting edge profile measurement results such as Figure 3 shown.

[0058] The cutting edge profile of the tool is established according to the tool geometric parameters, specifically:

[0059] R t =R ideal +ΔR wave =R ideal +Δwsin(ωθ)

[0060] In the formula, R ideal is the ideal cutting edge profile of the tool, and Δw is the cutting edge waviness amplitude.

[0061] Among them, the ideal cutting edge profile of the arc-shaped tool with a radius of r can be calculated by the following formula:

[0062]

[0063] The blade tip angle is The ideal cutting edge profile of a V-tip knife can be calculated by the following formula:

[0064]

[0065] Where h is the cutting depth.

[0066] Measure the characteristic parameters of the workpiece material, including elastic modulus, Poisson's ratio, hardness, and yield strength. Calculate the contour deformation caused by the elastic recovery of the material based on the processing parameters and the characteristic parameters of the workpiece material to be cut. The contour deformation caused by the elastic recovery of the material includes the elastic recovery caused by the cutting force and the elastic recovery caused by the blunt edge. The schematic diagram of the influence of the elastic recovery component on the cross-sectional profile is shown in Figure 4 The following formula is used to calculate the contour deformation caused by the elastic recovery of the material:

[0067] e=e1+e2

[0068] Where e1 is the elastic recovery caused by cutting force, and e2 is the elastic recovery caused by the blunt edge.

[0069] The elastic recovery caused by the cutting force corresponding to e1 is simplified into a linear transformation, and its maximum elastic deformation δ is calculated using the following formula:

[0070]

[0071] Where P is the load on the workpiece, E * is the equivalent elastic modulus, and R is the radius of the equivalent sphere.

[0072] The elastic recovery e2 caused by the blunt edge is the same everywhere along the microstructure cross-sectional profile, and the springback e2 is calculated using the following formula:

[0073] e2=(1-ε p )·h min

[0074] In the formula, h min is the minimum cutting thickness, ε p is the plastic strain.

[0075] According to the stress-strain relationship in the elastic-plastic deformation theory, the plastic strain is calculated. σ t is the yield strength of the workpiece, and E is the elastic modulus.

[0076] The contour deformation caused by plastic lateral flow includes the reduction of microgroove width caused by plastic lateral flow and the material accumulation at the microgroove boundary caused by plastic lateral flow.

[0077] According to the machining parameters, tool geometry parameters and characteristic parameters of the workpiece material to be cut, the reduction in microgroove width and the material accumulation at the microgroove boundary caused by the plastic lateral flow are calculated. The schematic diagram of the influence of the plastic lateral flow component on the cross-sectional profile is shown in Figure 5 The calculation formula for the reduction in microgroove width caused by plastic lateral flow is as follows:

[0078] s=k c k m kt h min L t

[0079] Among them, k c is the correction factor, k m is a coefficient determined by material properties, k t is a coefficient determined by the tool size, L t is the cutting width of the tool.

[0080] Material accumulation height Δh at the microgroove boundary a The calculation is done using the following formula:

[0081]

[0082] in, Represents the equivalent half apex angle of the diamond tool.

[0083] According to the influence of the calculated processing parameters on the deformation of the micro-groove profile, the cutting depth is pre-compensated before processing, and appropriate processing parameters are selected to reduce the processing surface morphology error caused by elastic-plastic deformation, and finally obtain a cutting surface with higher precision.

[0084] Use correction factor to correct (correction factor is obtained by experiment, the specific selection is as follows Figure 6 The influence of machining parameters on the elastic-plastic deformation, including cutting depth, cutting speed and workpiece material, is calculated as follows:

[0085] R model =R t +f d f s f m (e+s+Δh a )

[0086] Among them, f d is the correction factor of the prediction model regarding cutting depth, f s is the correction factor of the prediction model for cutting speed, f m is the correction factor of the prediction model for the workpiece material. Figure 6 , which is a schematic diagram of selecting correction coefficients according to different processing parameters in the model of the present invention.

[0087] The solution of this application is explained and verified by using specific examples below.

[0088] Example 1:

[0089] The ultra-precision turning microgroove test was carried out to verify the present invention. The workpiece material was oxygen-free copper TU2, the processing equipment was a three-axis ultra-precision machining lathe, and the tool was a nominal 100μm arc-shaped single-point diamond tool. At a cutting speed of 5mm·min-1, a microgroove with a depth of 6μm was machined on the workpiece. The microgroove cross-sectional profiles of the actual processing, the common model and the present model, as well as the difference between the predicted results of the common model and the present model and the actual processing results are shown in Figure 2. Figure 7 shown.

[0090] After measurement, the arc radius of the tool is 100.95μm, the front angle and back angle are 0° and 10° respectively, the waviness is 55nm, the blunt radius of the cutting edge is 50nm, and the actual cutting depth is 6.76μm.

[0091] Compared with the prediction results of the ordinary model: the average error of the ordinary model is 0.50μm, and the maximum error is 1.15μm; the average error predicted by this model is 0.06μm, and the maximum error is 0.25μm.

[0092] Example 2:

[0093] The ultra-precision turning microgroove test was carried out to verify the present invention. The workpiece material was brass H59, the processing equipment was a three-axis ultra-precision machining lathe, and the tool was a nominal 50μm arc-shaped single-point diamond tool. At a cutting speed of 200mm·min-1, a microgroove with a depth of 6μm was machined on the workpiece. The microgroove cross-sectional profiles of the actual processing, the common model and the present model, as well as the difference between the predicted results of the common model and the present model and the actual processing results are shown in Figure 2. Figure 8 shown.

[0094] After measurement, the arc radius of the tool is 51.69μm, the front angle and back angle are 0° and 10° respectively, the waviness is 39nm, the blunt radius of the cutting edge is 50nm, and the actual cutting depth is 6.70μm.

[0095] Compared with the prediction results of the ordinary model: the average error of the ordinary model is 0.16μm, and the maximum error is 1.08μm; the average error predicted by this model is 0.06μm, and the maximum error is 0.23μm.

[0096] Example 3:

[0097] The ultra-precision turning microgroove test was carried out to verify the present invention. The workpiece material was aluminum alloy 6061, the processing equipment was a three-axis ultra-precision machining lathe, and the tool was a V-shaped single-point diamond tool with a nominal angle of 140°. At a cutting speed of 50 mm·min-1, a microgroove with a depth of 6 μm was machined on the workpiece. The microgroove cross-sectional profiles of the actual machining, the common model and the present model, as well as the difference between the predicted results of the common model and the present model and the actual machining results are shown in Figure 2. Fig. 9 shown.

[0098] After measurement, the angle of the tool is 139.92°, the front angle and back angle are 0° and 10° respectively, the waviness is 36nm, the blunt radius of the cutting edge is 50nm, and the actual cutting depth is 7.55μm.

[0099] Ignoring the influence of micro-chipping at the tool tip, compared with the prediction results of the ordinary model: the average error predicted by the ordinary model is 0.34μm, and the maximum error is 0.72μm; the average error predicted by this model is 0.08μm, and the maximum error is 0.30μm.

[0100] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface, characterized in that: The following steps are involved: Obtaining machining parameters, tool geometry parameters and characteristic parameters of the workpiece material to be cut; The cutting edge profile of the tool is established according to the tool geometric parameters, the profile deformation caused by the elastic recovery of the material is calculated according to the processing parameters and the characteristic parameters of the workpiece material to be cut, and the profile deformation caused by the plastic lateral flow is calculated according to the processing parameters, the tool geometric parameters and the characteristic parameters of the workpiece material to be cut; Based on the cutting edge profile of the tool, the deformation caused by the elastic recovery of the material, and the deformation caused by the plastic lateral flow, the correction coefficient of the morphology prediction model under different processing parameters is calculated to obtain the cutting surface geometric morphology prediction model; The machining parameters are optimized and modified, and the elastic-plastic deformation is pre-compensated to obtain the final cutting surface.

2. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 1, characterized in that: The cutting edge profile of the tool is established according to the tool geometric parameters, specifically: R t =R ideal +ΔR wave =R ideal +Δwsin(ωθ) Among them, R ideal is the ideal cutting edge profile of the tool, and Δw is the cutting edge waviness amplitude.

3. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 2, characterized in that: The ideal cutting edge profile of a circular arc tool with a radius of r can be calculated as follows: The blade tip angle is The ideal cutting edge profile of a V-tip knife can be calculated by the following formula: Where h is the cutting depth.

4. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 1, characterized in that: The contour deformation caused by the elastic recovery of the material includes the elastic recovery caused by the cutting force and the elastic recovery caused by the blunting of the cutting edge.

5. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 1, characterized in that: The contour deformation caused by plastic lateral flow includes the reduction of microgroove width caused by plastic lateral flow and the material accumulation at the microgroove boundary caused by plastic lateral flow.

6. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 1, characterized in that: The final cutting surface geometry prediction model is: R model =R t +f d f s f m (e+s+Δh a ) Among them, f d is the correction factor of the prediction model regarding cutting depth, f s is the correction factor of the prediction model for cutting speed, f m is the correction factor of the prediction model regarding the workpiece material.

7. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 2, characterized in that: The tool geometric parameters include the arc radius of the arc-shaped tool, the angle of the V-shaped tip, the front angle and the back angle of the tool, and the waviness of the cutting edge profile.

8. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 1, characterized in that: The characteristic parameters of the workpiece material to be cut include elastic modulus, Poisson's ratio, hardness and yield strength.

9. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 5, characterized in that: The calculation formula for the material accumulation height at the microgroove boundary caused by plastic lateral flow is: Where θ represents the equivalent half-apex angle of the diamond tool.

10. The method for predicting the geometric morphology and machining accuracy of an ultra-precision cutting surface according to claim 5, characterized in that: The calculation formula for the reduction in microgroove width caused by plastic lateral flow is: s=k c k m k t h min L t Among them, k c is the correction factor, k m is a coefficient determined by material properties, k t is a coefficient determined by the tool size, L t is the cutting width of the tool.

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